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Metoda syntetycznej kontroli (SCM)×Metoda regresji z nieciągłością (RDD)×
DziedzinaWnioskowanie przyczynoweWnioskowanie przyczynowe
RodzinaRegression modelRegression model
Rok powstania20102008
TwórcaAbadie, Diamond & HainmuellerImbens & Lemieux (guide to practice); Cattaneo, Idrobo & Titiunik (practical introduction)
TypCounterfactual causal-inference modelQuasi-experimental causal design
Źródło pierwotneAbadie, A., Diamond, A., & Hainmueller, J. (2010). Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California's Tobacco Control Program. Journal of the American Statistical Association, 105(490), 493-505. DOI ↗Imbens, G. W., & Lemieux, T. (2008). Regression Discontinuity Designs: A Guide to Practice. Journal of Econometrics, 142(2), 615-635. DOI ↗
Inne nazwysynthetic control method, SCM, synthetic counterfactual, Sentetik Kontrol Yöntemi (SCM)RDD, regression discontinuity design, sharp RDD, fuzzy RDD
Pokrewne55
PodsumowanieThe Synthetic Control Method, introduced by Abadie, Diamond and Hainmueller in 2010, builds a weighted counterfactual for a single treated unit from a pool of untreated donor units. It is widely regarded as the gold standard for evaluating large policy interventions, natural experiments, and N=1 case studies where no obvious comparison unit exists.Regression Discontinuity Design is a quasi-experimental method that identifies a causal effect by locally comparing units just above and just below a cutoff on a continuous assignment (running) variable. Formalised for applied work by Imbens and Lemieux (2008) and developed as a practical framework by Cattaneo, Idrobo, and Titiunik (2020), it estimates a local average treatment effect (LATE) at the threshold.
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ScholarGatePorównaj metody: Synthetic Control · Regression Discontinuity. Pobrano 2026-06-18 z https://scholargate.app/pl/compare